Overview

Dataset statistics

Number of variables12
Number of observations2969
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory301.5 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtde_invoices is highly overall correlated with gross_revenue and 3 other fieldsHigh correlation
qtde_item is highly overall correlated with avg_basket_size and 2 other fieldsHigh correlation
qtde_products is highly overall correlated with avg_unique_basket_size and 2 other fieldsHigh correlation
recency_days is highly overall correlated with qtde_invoicesHigh correlation
qtde_item is highly skewed (γ1 = 28.46941323)Skewed
avg_ticket is highly skewed (γ1 = 53.44422362)Skewed
frequency is highly skewed (γ1 = 24.88049136)Skewed
qtde_returns is highly skewed (γ1 = 51.79774426)Skewed
avg_basket_size is highly skewed (γ1 = 44.67271661)Skewed
customer_id has unique valuesUnique
recency_days has 34 (1.1%) zerosZeros
qtde_returns has 1481 (49.9%) zerosZeros

Reproduction

Analysis started2024-07-13 21:48:08.391069
Analysis finished2024-07-13 21:48:28.878856
Duration20.49 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

UNIQUE 

Distinct2969
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15270.773
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:28.980857image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12619.4
Q113799
median15221
Q316768
95-th percentile17964.6
Maximum18287
Range5940
Interquartile range (IQR)2969

Descriptive statistics

Standard deviation1718.9903
Coefficient of variation (CV)0.11256734
Kurtosis-1.2060947
Mean15270.773
Median Absolute Deviation (MAD)1488
Skewness0.031607859
Sum45338925
Variance2954927.6
MonotonicityNot monotonic
2024-07-13T18:48:29.139857image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17850 1
 
< 0.1%
17588 1
 
< 0.1%
14905 1
 
< 0.1%
16103 1
 
< 0.1%
14626 1
 
< 0.1%
14868 1
 
< 0.1%
18246 1
 
< 0.1%
17115 1
 
< 0.1%
16611 1
 
< 0.1%
15912 1
 
< 0.1%
Other values (2959) 2959
99.7%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18269 1
< 0.1%

gross_revenue
Real number (ℝ)

HIGH CORRELATION 

Distinct2954
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2749.3217
Minimum6.2
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:29.301856image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile229.77
Q1570.96
median1086.92
Q32308.06
95-th percentile7219.68
Maximum279138.02
Range279131.82
Interquartile range (IQR)1737.1

Descriptive statistics

Standard deviation10580.623
Coefficient of variation (CV)3.8484486
Kurtosis353.94472
Mean2749.3217
Median Absolute Deviation (MAD)672.16
Skewness16.777556
Sum8162736.2
Variance1.1194959 × 108
MonotonicityNot monotonic
2024-07-13T18:48:29.462857image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
178.96 2
 
0.1%
533.33 2
 
0.1%
889.93 2
 
0.1%
2053.02 2
 
0.1%
745.06 2
 
0.1%
379.65 2
 
0.1%
2092.32 2
 
0.1%
731.9 2
 
0.1%
1353.74 2
 
0.1%
331 2
 
0.1%
Other values (2944) 2949
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
13.3 1
< 0.1%
15 1
< 0.1%
36.56 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
168472.5 1
< 0.1%
140450.72 1
< 0.1%
124564.53 1
< 0.1%
117379.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%

recency_days
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct272
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.287639
Minimum0
Maximum373
Zeros34
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:29.619856image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median31
Q381
95-th percentile242
Maximum373
Range373
Interquartile range (IQR)70

Descriptive statistics

Standard deviation77.756779
Coefficient of variation (CV)1.2095137
Kurtosis2.7779627
Mean64.287639
Median Absolute Deviation (MAD)26
Skewness1.7983795
Sum190870
Variance6046.1167
MonotonicityNot monotonic
2024-07-13T18:48:29.786857image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.3%
4 87
 
2.9%
2 85
 
2.9%
3 85
 
2.9%
8 76
 
2.6%
10 67
 
2.3%
9 66
 
2.2%
7 66
 
2.2%
17 64
 
2.2%
16 55
 
1.9%
Other values (262) 2219
74.7%
ValueCountFrequency (%)
0 34
 
1.1%
1 99
3.3%
2 85
2.9%
3 85
2.9%
4 87
2.9%
5 43
1.4%
7 66
2.2%
8 76
2.6%
9 66
2.2%
10 67
2.3%
ValueCountFrequency (%)
373 2
0.1%
372 4
0.1%
371 1
 
< 0.1%
368 1
 
< 0.1%
366 4
0.1%
365 2
0.1%
364 1
 
< 0.1%
360 1
 
< 0.1%
359 1
 
< 0.1%
358 4
0.1%

qtde_invoices
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7231391
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:29.960856image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile17
Maximum206
Range205
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.8565313
Coefficient of variation (CV)1.5474954
Kurtosis190.83445
Mean5.7231391
Median Absolute Deviation (MAD)2
Skewness10.766805
Sum16992
Variance78.438147
MonotonicityNot monotonic
2024-07-13T18:48:30.119856image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 785
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
1 190
 
6.4%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
Other values (46) 332
11.2%
ValueCountFrequency (%)
1 190
 
6.4%
2 785
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

qtde_item
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct747
Distinct (%)25.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean384.94038
Minimum1
Maximum80996
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:30.274856image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile35
Q185
median154
Q3293
95-th percentile932.2
Maximum80996
Range80995
Interquartile range (IQR)208

Descriptive statistics

Standard deviation1941.885
Coefficient of variation (CV)5.0446383
Kurtosis1064.3611
Mean384.94038
Median Absolute Deviation (MAD)86
Skewness28.469413
Sum1142888
Variance3770917.4
MonotonicityNot monotonic
2024-07-13T18:48:30.462812image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60 28
 
0.9%
70 26
 
0.9%
67 24
 
0.8%
66 23
 
0.8%
90 22
 
0.7%
120 22
 
0.7%
52 21
 
0.7%
69 19
 
0.6%
75 19
 
0.6%
84 19
 
0.6%
Other values (737) 2746
92.5%
ValueCountFrequency (%)
1 3
0.1%
3 2
 
0.1%
6 2
 
0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 4
0.1%
11 1
 
< 0.1%
12 6
0.2%
13 1
 
< 0.1%
15 2
 
0.1%
ValueCountFrequency (%)
80996 1
< 0.1%
38639 1
< 0.1%
21352 1
< 0.1%
17376 1
< 0.1%
17150 1
< 0.1%
16288 1
< 0.1%
15837 1
< 0.1%
13369 1
< 0.1%
12872 1
< 0.1%
10827 1
< 0.1%

qtde_products
Real number (ℝ)

HIGH CORRELATION 

Distinct341
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.323678
Minimum1
Maximum1786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:30.635812image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q126
median52
Q3101
95-th percentile233.6
Maximum1786
Range1785
Interquartile range (IQR)75

Descriptive statistics

Standard deviation96.855131
Coefficient of variation (CV)1.2210116
Kurtosis82.402998
Mean79.323678
Median Absolute Deviation (MAD)33
Skewness6.3900489
Sum235512
Variance9380.9164
MonotonicityNot monotonic
2024-07-13T18:48:30.801812image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 44
 
1.5%
37 39
 
1.3%
18 39
 
1.3%
28 39
 
1.3%
25 37
 
1.2%
26 37
 
1.2%
11 36
 
1.2%
15 36
 
1.2%
14 36
 
1.2%
30 36
 
1.2%
Other values (331) 2590
87.2%
ValueCountFrequency (%)
1 25
0.8%
2 16
0.5%
3 21
0.7%
4 20
0.7%
5 33
1.1%
6 23
0.8%
7 25
0.8%
8 30
1.0%
9 32
1.1%
10 27
0.9%
ValueCountFrequency (%)
1786 1
< 0.1%
1766 1
< 0.1%
1322 1
< 0.1%
1118 1
< 0.1%
884 1
< 0.1%
817 1
< 0.1%
717 1
< 0.1%
714 1
< 0.1%
699 1
< 0.1%
636 1
< 0.1%

avg_ticket
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2966
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.897762
Minimum2.1505882
Maximum56157.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:30.961813image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum2.1505882
5-th percentile4.9166611
Q113.119333
median17.956587
Q324.988286
95-th percentile90.497
Maximum56157.5
Range56155.349
Interquartile range (IQR)11.868952

Descriptive statistics

Standard deviation1036.9344
Coefficient of variation (CV)19.98033
Kurtosis2890.7071
Mean51.897762
Median Absolute Deviation (MAD)5.984842
Skewness53.444224
Sum154084.45
Variance1075233
MonotonicityNot monotonic
2024-07-13T18:48:31.119813image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 2
 
0.1%
4.162 2
 
0.1%
14.47833333 2
 
0.1%
18.15222222 1
 
< 0.1%
13.92736842 1
 
< 0.1%
36.24411765 1
 
< 0.1%
29.78416667 1
 
< 0.1%
22.8792623 1
 
< 0.1%
20.51104167 1
 
< 0.1%
149.025 1
 
< 0.1%
Other values (2956) 2956
99.6%
ValueCountFrequency (%)
2.150588235 1
< 0.1%
2.4325 1
< 0.1%
2.462371134 1
< 0.1%
2.511241379 1
< 0.1%
2.515333333 1
< 0.1%
2.65 1
< 0.1%
2.656931818 1
< 0.1%
2.707598253 1
< 0.1%
2.760621572 1
< 0.1%
2.770464191 1
< 0.1%
ValueCountFrequency (%)
56157.5 1
< 0.1%
4453.43 1
< 0.1%
3202.92 1
< 0.1%
1687.2 1
< 0.1%
952.9875 1
< 0.1%
872.13 1
< 0.1%
841.0214493 1
< 0.1%
651.1683333 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%

avg_recency_days
Real number (ℝ)

HIGH CORRELATION 

Distinct1258
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-67.348511
Minimum-366
Maximum-1
Zeros0
Zeros (%)0.0%
Negative2969
Negative (%)100.0%
Memory size46.4 KiB
2024-07-13T18:48:31.279813image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-366
5-th percentile-201
Q1-85.333333
median-48.285714
Q3-25.923077
95-th percentile-8
Maximum-1
Range365
Interquartile range (IQR)59.410256

Descriptive statistics

Standard deviation63.544929
Coefficient of variation (CV)-0.94352388
Kurtosis4.8871091
Mean-67.348511
Median Absolute Deviation (MAD)26.285714
Skewness-2.0627709
Sum-199957.73
Variance4037.958
MonotonicityNot monotonic
2024-07-13T18:48:31.454813image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-14 25
 
0.8%
-4 22
 
0.7%
-70 21
 
0.7%
-7 20
 
0.7%
-35 19
 
0.6%
-49 18
 
0.6%
-46 17
 
0.6%
-21 17
 
0.6%
-11 17
 
0.6%
-42 16
 
0.5%
Other values (1248) 2777
93.5%
ValueCountFrequency (%)
-366 1
 
< 0.1%
-365 1
 
< 0.1%
-363 1
 
< 0.1%
-362 1
 
< 0.1%
-357 2
0.1%
-356 1
 
< 0.1%
-355 2
0.1%
-352 1
 
< 0.1%
-351 2
0.1%
-350 3
0.1%
ValueCountFrequency (%)
-1 16
0.5%
-1.5 1
 
< 0.1%
-2 13
0.4%
-2.5 1
 
< 0.1%
-2.601398601 1
 
< 0.1%
-3 15
0.5%
-3.321428571 1
 
< 0.1%
-3.330357143 1
 
< 0.1%
-3.5 2
 
0.1%
-4 22
0.7%

frequency
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1225
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1137973
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:31.619812image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0088941642
Q10.016339869
median0.025889968
Q30.049450549
95-th percentile1
Maximum17
Range16.99455
Interquartile range (IQR)0.03311068

Descriptive statistics

Standard deviation0.40815625
Coefficient of variation (CV)3.5866953
Kurtosis989.36508
Mean0.1137973
Median Absolute Deviation (MAD)0.012191338
Skewness24.880491
Sum337.8642
Variance0.16659153
MonotonicityNot monotonic
2024-07-13T18:48:32.105813image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 198
 
6.7%
0.0625 18
 
0.6%
0.02777777778 17
 
0.6%
0.02380952381 16
 
0.5%
0.09090909091 15
 
0.5%
0.08333333333 15
 
0.5%
0.03448275862 14
 
0.5%
0.02941176471 14
 
0.5%
0.03571428571 13
 
0.4%
0.07692307692 13
 
0.4%
Other values (1215) 2636
88.8%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
3 1
 
< 0.1%
2 6
 
0.2%
1.142857143 1
 
< 0.1%
1 198
6.7%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%
0.5 3
 
0.1%

qtde_returns
Real number (ℝ)

SKEWED  ZEROS 

Distinct214
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.156955
Minimum0
Maximum80995
Zeros1481
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:32.274813image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q39
95-th percentile100.6
Maximum80995
Range80995
Interquartile range (IQR)9

Descriptive statistics

Standard deviation1512.4961
Coefficient of variation (CV)24.333498
Kurtosis2765.5286
Mean62.156955
Median Absolute Deviation (MAD)1
Skewness51.797744
Sum184544
Variance2287644.6
MonotonicityNot monotonic
2024-07-13T18:48:32.456812image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
49.9%
1 164
 
5.5%
2 148
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
6 78
 
2.6%
5 61
 
2.1%
12 51
 
1.7%
8 43
 
1.4%
7 43
 
1.4%
Other values (204) 706
23.8%
ValueCountFrequency (%)
0 1481
49.9%
1 164
 
5.5%
2 148
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
5 61
 
2.1%
6 78
 
2.6%
7 43
 
1.4%
8 43
 
1.4%
9 41
 
1.4%
ValueCountFrequency (%)
80995 1
< 0.1%
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%

avg_basket_size
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1979
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.81376
Minimum1
Maximum40498.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:32.647641image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44
Q1103.25
median172.33333
Q3281.69231
95-th percentile600
Maximum40498.5
Range40497.5
Interquartile range (IQR)178.44231

Descriptive statistics

Standard deviation791.55519
Coefficient of variation (CV)3.1685812
Kurtosis2255.5382
Mean249.81376
Median Absolute Deviation (MAD)83.083333
Skewness44.672717
Sum741697.07
Variance626559.62
MonotonicityNot monotonic
2024-07-13T18:48:32.836641image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
114 10
 
0.3%
73 9
 
0.3%
82 9
 
0.3%
86 9
 
0.3%
60 8
 
0.3%
88 8
 
0.3%
75 8
 
0.3%
136 8
 
0.3%
208 7
 
0.2%
Other values (1969) 2882
97.1%
ValueCountFrequency (%)
1 2
0.1%
2 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
40498.5 1
< 0.1%
6009.333333 1
< 0.1%
4282 1
< 0.1%
3906 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2801 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

HIGH CORRELATION 

Distinct1005
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.154708
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-07-13T18:48:33.012640image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.3454545
Q110
median17.2
Q327.75
95-th percentile56.94
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation19.512322
Coefficient of variation (CV)0.88073027
Kurtosis27.703297
Mean22.154708
Median Absolute Deviation (MAD)8.2
Skewness3.4994559
Sum65777.329
Variance380.73071
MonotonicityNot monotonic
2024-07-13T18:48:33.182640image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 53
 
1.8%
14 39
 
1.3%
11 38
 
1.3%
20 33
 
1.1%
9 33
 
1.1%
1 32
 
1.1%
17 31
 
1.0%
18 30
 
1.0%
10 30
 
1.0%
5 29
 
1.0%
Other values (995) 2621
88.3%
ValueCountFrequency (%)
1 32
1.1%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 8
 
0.3%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 24
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
259 1
< 0.1%
203.5 1
< 0.1%
148 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
127 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%

Interactions

2024-07-13T18:48:26.921246image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:08.696213image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:10.505922image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:12.051547image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:13.664400image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:15.122709image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:17.043783image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:18.638057image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:20.208360image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:21.827379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:23.699378image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:25.315889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:27.052245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:08.834213image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:10.635436image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:12.171544image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:13.780945image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:15.251478image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:17.161325image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:18.773057image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:20.329359image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:21.965379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:23.828869image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:25.447889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:27.184245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:08.956213image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:10.754641image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:12.293545image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:13.892971image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:15.372993image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:17.293594image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:18.905057image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:20.462361image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:22.083379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:23.960319image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:25.572889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:27.345244image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:09.113213image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:10.885008image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:12.434545image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:14.012512image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:15.503025image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:17.419186image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:19.047078image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:20.599359image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:22.209379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:24.101348image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:25.704889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:27.458245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:09.246214image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:10.996007image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:12.552570image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:14.116538image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:15.621572image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:17.540187image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:19.171078image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:20.724360image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:22.332379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:24.222348image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:25.823889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:27.586245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:09.408263image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:11.136008image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:12.701570image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:14.249053image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:15.977193image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:17.679187image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:19.310079image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:20.867360image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:22.470380image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:24.367348image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:25.966889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:27.712245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:09.535263image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:11.278009image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:12.836570image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:14.370085image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:16.112730image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:17.826214image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:19.446070image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:21.006360image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:22.626378image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:24.511348image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:26.103245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:27.827245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:09.659265image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:11.400031image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:12.965991image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:14.482111image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:16.232731image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:17.963214image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:19.563360image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:21.128361image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:22.753379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:24.633889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:26.230246image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:27.952245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:09.784296image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:11.534030image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:13.094778image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:14.610141image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:16.379271image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:18.098213image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:19.699360image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:21.256359image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:22.895378image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:24.767889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:26.367245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:28.077246image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:10.088328image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:11.662545image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:13.225144image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:14.738701image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:16.526783image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:18.222517image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:19.823360image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:21.387360image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:23.023379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:24.910889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:26.502245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:28.214226image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:10.235327image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:11.795545image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:13.399864image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:14.868727image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:16.766785image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:18.355517image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:19.960359image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:21.538108image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:23.158379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:25.044889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:26.644245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:28.349857image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:10.376896image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:11.929544image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:13.537375image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:14.995275image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:16.915783image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:18.500545image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:20.088360image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:21.689378image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:23.300379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:25.183889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-13T18:48:26.784245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Correlations

2024-07-13T18:48:33.311640image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygross_revenueqtde_invoicesqtde_itemqtde_productsqtde_returnsrecency_days
avg_basket_size1.0000.0770.1880.447-0.1230.0270.5740.1000.6710.3850.210-0.098
avg_recency_days0.0771.0000.122-0.048-0.0190.8810.2470.2590.1670.1130.396-0.108
avg_ticket0.1880.1221.000-0.611-0.1310.0900.2460.0590.344-0.4560.1900.048
avg_unique_basket_size0.447-0.048-0.6111.000-0.007-0.0720.2910.0250.0620.7770.019-0.106
customer_id-0.123-0.019-0.131-0.0071.000-0.002-0.0760.026-0.0430.007-0.0630.001
frequency0.0270.8810.090-0.072-0.0021.0000.0900.0790.059-0.0030.2340.018
gross_revenue0.5740.2470.2460.291-0.0760.0901.0000.7700.7080.6640.372-0.415
qtde_invoices0.1000.2590.0590.0250.0260.0790.7701.0000.5280.5830.294-0.502
qtde_item0.6710.1670.3440.062-0.0430.0590.7080.5281.0000.3480.257-0.290
qtde_products0.3850.113-0.4560.7770.007-0.0030.6640.5830.3481.0000.207-0.380
qtde_returns0.2100.3960.1900.019-0.0630.2340.3720.2940.2570.2071.000-0.120
recency_days-0.098-0.1080.048-0.1060.0010.018-0.415-0.502-0.290-0.380-0.1201.000

Missing values

2024-07-13T18:48:28.515856image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-13T18:48:28.755856image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysqtde_invoicesqtde_itemqtde_productsavg_ticketavg_recency_daysfrequencyqtde_returnsavg_basket_sizeavg_unique_basket_size
0178505391.21372.034.035.021.018.152222-35.50000017.00000040.050.9705888.735294
1130473232.5956.09.0131.0105.018.904035-27.2500000.02830235.0154.44444419.000000
2125836705.382.015.01568.0114.028.902500-23.1875000.04032350.0335.20000015.466667
313748948.2595.05.0169.024.033.866071-92.6666670.0179210.087.8000005.600000
415100876.00333.03.048.01.0292.000000-8.6000000.07317122.026.6666671.000000
5152914623.3025.014.0508.061.045.326471-23.2000000.04011529.0150.1428577.285714
6146885630.877.021.0579.0148.017.219786-18.3000000.057221399.0172.42857115.571429
7178095411.9116.012.0961.046.088.719836-35.7000000.03352041.0171.4166675.083333
81531160767.900.091.02167.0567.025.543464-4.1444440.243316474.0419.71428626.142857
9160982005.6387.07.0240.034.029.934776-47.6666670.0243900.087.5714299.571429
customer_idgross_revenuerecency_daysqtde_invoicesqtde_itemqtde_productsavg_ticketavg_recency_daysfrequencyqtde_returnsavg_basket_sizeavg_unique_basket_size
5627177271060.2515.01.0111.066.016.064394-6.01.0000006.0645.00000066.0
563717232421.522.02.066.030.011.708889-12.00.1538460.0101.50000018.0
563817468137.0010.02.044.05.027.400000-4.00.4000000.058.0000002.5
564913596697.045.02.081.0133.04.199036-7.00.2500000.0203.00000083.0
5655148931237.859.02.0226.072.016.956849-2.00.6666670.0399.50000036.5
565912479473.2011.01.087.030.015.773333-4.01.00000034.0382.00000030.0
568014126706.137.03.0361.014.047.075333-3.00.75000050.0169.3333335.0
5686135211092.391.03.046.0312.02.511241-4.50.3000000.0244.333333145.0
569615060301.848.04.057.080.02.515333-1.02.0000000.065.50000030.0
571512558269.967.01.0102.011.024.541818-6.01.000000196.0196.00000011.0